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17-07-2021

Pricing commodity-linked bonds with stochastic convenience yield, interest rate and counterparty credit risk: application of Mellin transform methods

Authors: Zonggang Ma, Chaoqun Ma, Zhijian Wu

Published in: Review of Derivatives Research | Issue 1/2022

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Abstract

The article 'Pricing commodity-linked bonds with stochastic convenience yield, interest rate and counterparty credit risk: application of Mellin transform methods' delves into the complexities of pricing commodity-linked bonds by incorporating various risk factors such as convenience yield, interest rates, and counterparty credit risk. The authors build upon existing frameworks, notably Schwartz (1982) and Carr (1987), to develop a more comprehensive model. They employ Mellin transform methods to derive closed-form pricing formulas, which significantly enhance the accuracy and efficiency of valuation. The paper introduces four models: a one-factor model focusing on spot commodity price risk, a two-factor model considering both spot price and convenience yield, and two three-factor models that additionally account for interest rate risk and counterparty credit risk. The closed-form solutions provided are expressed using standard normal cumulative distribution functions, facilitating rapid and accurate pricing and hedging of commodity-linked bonds. Numerical examples and sensitivity analyses are presented to illustrate the impact of various parameters on bond prices, highlighting the significance of convenience yield, interest rates, and counterparty credit risk. This article is a must-read for professionals seeking to understand the intricacies of commodity-linked bond pricing and the application of advanced mathematical techniques in finance.

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Metadata
Title
Pricing commodity-linked bonds with stochastic convenience yield, interest rate and counterparty credit risk: application of Mellin transform methods
Authors
Zonggang Ma
Chaoqun Ma
Zhijian Wu
Publication date
17-07-2021
Publisher
Springer US
Published in
Review of Derivatives Research / Issue 1/2022
Print ISSN: 1380-6645
Electronic ISSN: 1573-7144
DOI
https://doi.org/10.1007/s11147-021-09181-9

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